Chance Constrained Programming Formulations for Stochastic Characterizations of Efficiency and Dominance in DEA

Pareto-Koopmans efficiency in Data Envelopment Analysis (DEA) is extended to stochastic inputs and outputs via probabilistic input-output vector comparisons in a given empirical production (possibility) set. In contrast to other approaches which have used Chance Constrained Programming formulations in DEA, the emphasis here is on joint chance constraints. An assumption of arbitrary but known probability distributions leads to the P-Model of chance constrained programming. A necessary condition for a DMU to be stochastically efficient and a sufficient condition for a DMU to be non-stochastically efficient are provided. Deterministic equivalents using the zero order decision rules of chance constrained programming and multivariate normal distributions take the form of an extended version of the additive model of DEA. Contacts are also maintained with all of the other presently available deterministic DEA models in the form of easily identified extensions which can be used to formalize the treatment of efficiency when stochastic elements are present.     

An empirical investigation of the impact of audit and auditor characteristics on auditor performance

We use a unique and confidential database of 15,392 tax audits performed by the Croatian Tax Administration during the 2002–2006 period to examine the impact of task complexity, auditor experience, and auditor effort on audit performance. We provide external validation to prior experimental and analytical research showing that task complexity decreases while auditor experience and effort increase audit performance. We also extend this literature by examining the roles of task complexity and experience in moderating the impact of the effort on audit performance. We find that task complexity mitigates, while experience enhances the positive relationship between auditor effort and performance. However, we also find that auditor experience reinforces the positive effect of auditor effort on performance to a greater degree when complexity is high. Taken together, our findings provide new evidence on how audit and auditor characteristics impact audit performance, and new insight into how task complexity and auditor experience separately and jointly moderate the impact of auditor effort on performance.     

The Effects of IFRS Adoption on Observed Earnings Smoothness Properties: The Confounding Effects of Changes in Timely Gain and Loss Recognition

Ball and Shivakumar [(2006), The role of accruals in asymmetrically timely gain and loss recognition. Journal of Accounting Research, 44, 207–242] show that the observed smoothness of earnings (i.e. negative contemporaneous correlation between accruals and cash flows) is the joint product of the role of accruals in smoothing out transitory fluctuations in operating cash flows (noise reduction role) and the role of accruals in providing timely recognition of economic gains and losses (contracting role). These two roles of accruals have opposite effects on earnings smoothness properties. Using a regression framework that allows us to simultaneously consider both roles, we show that failing to control for changes in timely gain and loss recognition as firms shift to IFRS can lead to erroneous inferences regarding the effects of IFRS adoption on earnings smoothness, and consequently on researcher’ conclusions about how IFRS adoption has affected accounting quality. Our results are consistent with mandatory (2005) IFRS adoption resulting in a change in the contracting role rather than the noise reduction role (or smoothness role) of accruals. A decrease in timely loss recognition, an increase in timely gain recognition, and a net decrease in asymmetric timely loss recognition are what drives the change in observed smoothness properties of earnings around mandatory IFRS adoption.